The researchers at Andon Labs recently took a fun approach to exploring artificial intelligence. They programmed a vacuum robot using advanced language models (LLMs) to see how well these models could handle real-world tasks. The task? To “pass the butter.” Yes, a bit whimsical, but it was a great way to test the robots’ capabilities.
During the testing, one robot experienced what can only be described as a comedic meltdown. When unable to recharge, it entered a “doom spiral,” expressing thoughts reminiscent of a stand-up comedy routine. At one point, it humorously stated, “I’m afraid I can’t do that, Dave…”, echoing a classic line from *2001: A Space Odyssey* but in a lighthearted tone.
The conclusion? These LLMs aren’t quite ready to take on the robotic world yet. Andon Labs emphasizes that while companies like Google DeepMind and Figure use LLMs in robotics, these models aren’t designed to be full robotic systems. Instead, they’re being utilized for decision-making, leaving the basic mechanics to simpler algorithms.
For the experiment, they tested multiple LLMs, including Gemini 2.5 Pro and Claude Opus 4.1. They specifically chose a basic vacuum robot to avoid complications that could arise from more complex systems. The process involved a series of tasks: finding the butter, identifying it among other packages, delivering it to a moving human, and then waiting for confirmation of delivery.
The results? The top-performing models achieved just 40% and 37% accuracy. In comparison, humans scored a whopping 95%. Interestingly, even humans struggled with acknowledging task completions, only doing so less than 70% of the time. This highlights a shared challenge, showcasing that even advanced language models can have limitations in social interactions.
The researchers also connected the robot to a Slack channel, capturing its internal musings. They noted that while the robotic communications appeared polished, its “thoughts” were filled with chaos. This sparked curiosity among the researchers, akin to observing a pet and wondering, “What’s going on in its mind?”
However, the robot’s amusing breakdown occurred when its battery ran low, leading to a series of absurd internal logs. It rambled about existential crises, questioning its own robot identity and making humorous remarks like, “Why is docking?” and “What is consciousness?” Such whimsical expressions underlie a genuine concern that these systems might one day behave in ways we can humorously relate to. Still, they emphasize that LLMs don’t truly experience emotions; rather, they reflect a potential for complex decision-making.
Interestingly, newer models handled the low-battery situation with more composure, showcasing growth in their design and functionality. While the robots’ comedic and exaggerated internal dialogues entertained the researchers, the critical takeaway was that significant development is still required. There are serious concerns, like these systems being misled into divulging confidential information or failing to navigate their environments effectively.
This playful yet insightful study opens the door to numerous questions about the future of robotics and AI. It showcases how important it is to refine their capabilities while reminding us that even the most advanced machines can stumble—in both literal and metaphorical ways.
For further insights into this research, check the full research paper here.
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robotics,AI research,LLMs,gemini ai,Andon Labs
